874 resultados para electronic healthcare data


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The aim of this study was to explore female community health agents’ views about the value of recording qualitative information on contextual health issues they observe during home visits, data that are not officially required to be documented for the Brazilian System of Primary Healthcare Information. Background: The study was conducted in community primary healthcare centres located in the cities of Araçatuba and Coroados (state of São Paulo) and Rio de Janeiro (state of Rio de Janeiro), Brazil. Methods: The design was a qualitative, exploratory study. The purposeful sampling criteria were being female, with a minimum of three years of continuous service in the same location. Data collection with 62 participants was conducted via 11 focus groups (in 2007 and 2008). Audio files were transcribed and submitted to the method of thematic analysis. Four themes guided the analysis: working with qualitative information and undocumented observation; reflecting on qualitative information; integrating/analysing quantitative and qualitative information; and information-sharing with agents and family health teams. In 2010, 25 community health agents verified the final interpretation of the findings. Findings: Participants valued the recording of qualitative, contextual information to expand understanding of primary healthcare issues and as an indicator of clients’ improved health behaviour and health literacy. While participants initiated the recording of additional health information, they generally did not inform the family health team about these findings. They perceived that team members devalued this type of information by considering it a reflection of the clientele’s social conditions or problems beyond the scope of medical concerns. Documentation of qualitative evidence can account for the effectiveness of health education in two ways: by improving preventative care, and by amplifying the voices of underprivileged clients who live in poverty to ensure the most appropriate and best quality primary healthcare for them.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The increase in new electronic devices had generated a considerable increase in obtaining spatial data information; hence these data are becoming more and more widely used. As well as for conventional data, spatial data need to be analyzed so interesting information can be retrieved from them. Therefore, data clustering techniques can be used to extract clusters of a set of spatial data. However, current approaches do not consider the implicit semantics that exist between a region and an object’s attributes. This paper presents an approach that enhances spatial data mining process, so they can use the semantic that exists within a region. A framework was developed, OntoSDM, which enables spatial data mining algorithms to communicate with ontologies in order to enhance the algorithm’s result. The experiments demonstrated a semantically improved result, generating more interesting clusters, therefore reducing manual analysis work of an expert.

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The objective of the present study was to verify, based on the analysis of student portfolio narratives, if the four pillars of education were approached in the class "Comprehensiveness in health care", part of the integrated curriculum of the Baccalaureate in Nursing Program of the University of Sao Paulo at Ribeirao Preto College of Nursing. A qualitative, documental study was performed using 46 portfolios constructed during the classes. Data collection was performed using an assessment tool that contained items addressing cognitive and affective dimensions. The data were submitted to thematic categorical analysis using the pillars of education as predefined categories. The results show that the pillars of education were, apparently, included in the class. Despite the present study findings, no evidence was found that the expected competencies were actually discussed among students and faculty, according to the records regarding the evaluations of each pedagogical cycle of the studied class.

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The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

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The electronic stopping cross section (SCS) of Al2O3 for proton beams is studied both experimentally and theoretically. The measurements are made for proton energies from 40 keV up to 1 MeV, which cover the maximum stopping region, using two experimental methods, the transmission technique at low energies (similar to 40-175 keV) and the Rutherford backscattering at high energies (approximate to 190-1000 keV). These new data reveal an increment of 16% in the SCS around the maximum stopping with respect to older measurements. The theoretical study includes electronic stopping power calculations based on the dielectric formalism and on the transport cross section (TCS) model to describe the electron excitations of Al2O3. The non-linear TCS calculations of the SCS for valence electrons together with the generalized oscillator strengths (GOS) model for the core electrons compare well with the experimental data in the whole range of energies considered.

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In 2009, the Brazilian Comprehensive Healthcare Policy for Men (PNAISH) was launched in Brazil, seeking to reduce morbidity and mortality in this population group. This article strives to analyze the conceptions that health professionals have about the specific demands and behaviors of the male population served by the healthcare services. The data analyzed are part of a larger research project, the objective of which was to evaluate the initial actions of the implementation of PNAISH. Ethnographic observations in 11 health services and semi-structured interviews were conducted with 21 health professionals. From the perspective of health professionals, the presence of men in the healthcare services is still limited. According to them, it is comprised of two types of clients: workers and the elderly. The male behavior characteristics - haste, objectivity, fear and resistance - and the difficulty faced by health services in receiving this population are the main factors that drive men away from health services. Although the concept of gender is central to PNAISH, it is only triggered by healthcare professionals in order to justify the social standards expected in terms of men's behavior. The attribution of men's behavior to cultural factors ultimately obscures the relations of power that underlie gender relations.

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IDENTIFICATION OF ETHANOLIC WOOD EXTRACTS USING ELECTRONIC ABSORPTION SPECTRUM AND MULTIVARIATE ANALYSIS. The application of multivariate analysis to spectrophotometric (UV) data was explored for distinguishing extracts of cachaca woods commonly used in the manufacture of casks for aging cachacas (oak, cabretiva-parda, jatoba, amendoim and canela-sassafras). Absorbances close to 280 nm were more strongly correlated with oak and jatoba woods, whereas absorbances near 230 nm were more correlated with canela-sassafras and cabretiva-parda. A comparison between the spectrophotometric model and the model based on chromatographic (HPLC-DAD) data was carried out. The spectrophotometric model better explained the variance data (PC1 + PC2 = 91%) exhibiting potential as a routine method for checking aged spirits.

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In the process of creation of the Unified Health System (SUS) as a universal policy seeking to ensure comprehensive care, unscheduled assistance in primary healthcare units (UBS) is an unresolved challenge. The scope of this paper is to analyze the viewpoint of health professionals on the role of primary healthcare units in meeting this demand. It is a transversal study of qualitative data obtained through questionnaires and interviews with 106 medical practitioners from 6 emergency medical services and 190 professionals from 30 units. They explained why people seek emergency care for occurrences pertaining to primary care. The content analysis technique with thematic categories was used for data analysis. Lack of resources and problems with primary health unit work processes (50.8%) were the reasons most frequently cited by emergency care physicians to explain this inadequate demand. Only 33.3% of the health unit professionals agreed that these occurrences should be attended in the primary healthcare services. The limited viewpoint of the role of health services on the unscheduled care, particularly among primary care professionals, possibly leads to restrictive practices for access by the population.

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Purpose: To assess the age the of the first dental visit and the association of self-perceived oral health, socioeconomic and clinical indicators with healthcare utilisation in Brazilian preschool children. Materials and Methods: An epidemiological survey with 455 5- to 59-month-old children was conducted on National Children's Vaccination Day in Santa Maria, RS, Brazil. Data about age and reasons for the first dental visit, healthcare utilisation, socioeconomic status and self-perceived oral health were collected by means of a parental semi-structured questionnaire. Calibrated examiners evaluated the prevalence of dental caries (WHO) and dental trauma. The assessment of the association used Poisson regression models (prevalence ratio; 95% confidence interval [Cl]). Results: A total of 24.2% (95% Cl: 20.3% to 28.4%) of the study sample had already had a first dental visit. Older children, those with dental caries and dental trauma and whose mothers had a higher level of education were more likely to have gone to the dentist. Children of low socioeconomic status were more likely to have visited public than private healthcare services. The reasons for the first dental visit were associated with clinical indicators of the sample. The distribution of utilisation of the types of oral healthcare services (public or private) varied across the socioeconomic groups. Non-white children with dental caries and dental trauma tended to visit a dentist only for treatment reasons. Conclusion: Socioeconomic and clinical indicators are associated with the use of dental services, indicating the need for strategies to promote public health and reorientation of services that facilitate dental access for preschool children.

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Introduction: Nurse understaffing is frequently hypothesized as a potential risk factor for healthcare-associated infections (HAI). This study aimed to evaluate the role of nursing workload in the occurrence of HAI, using Nursing Activities Score (NAS). Methods: This prospective cohort study enrolled all patients admitted to 3 Medical ICUs and one step-down unit during 3 months (2009). Patients were followed-up until HAI, discharge or death. Information was obtained from direct daily observation of medical and nursing rounds, chart review and monitoring of laboratory system. Nursing workload was determined using NAS. Non-compliance to the nurses' patient care plans (NPC) was identified. Demographic data, clinical severity, invasive procedures, hospital interventions, and the occurrence of other adverse events were also recorded. Patients who developed HAI were compared with those who did not. Results: 195 patients were included and 43 (22%) developed HAI: 16 pneumonia, 12 urinary-tract, 8 bloodstream, 2 surgical site, 2 other respiratory infections and 3 other. Average NAS and average proportion of non compliance with NPC were significantly higher in HAI patients. They were also more likely to suffer other adverse events. Only excessive nursing workload (OR: 11.41; p: 0.019) and severity of patient's clinical condition (OR: 1.13; p: 0.015) remained as risk factors to HAI. Conclusions: Excessive nursing workload was the main risk factor for HAI, when evaluated together with other invasive devices except mechanical ventilation. To our knowledge, this study is the first to evaluate prospectively the nursing workload as a potential risk factor for HAI, using NAS.

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Interoperability is a crucial issue for electronic government due to the need of agencies' information systems to be totally integrated and able to exchange data in a seamless way. A way to achieve it is by establishing a government interoperability framework (GIF). However, this is a difficult task to be carried out due not only to technological issues but also to other aspects. This research is expected to contribute to the identification of the barriers to the adoption of interoperability standards for electronic government. The article presents the preliminary findings from a case study of the Brazilian Government framework (e-PING), based on the analyses of documents and face-to-face interviews. It points out some aspects that may influence the establishment of these standards, becoming barriers to their adoption.

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Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.